R Notebook
library(Seurat)Registered S3 method overwritten by 'data.table':
method from
print.data.table
Registered S3 method overwritten by 'htmlwidgets':
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print.htmlwidget tools:rstudio
Attaching SeuratObjectlibrary(SeuratDisk)Registered S3 method overwritten by 'SeuratDisk':
method from
as.sparse.H5Group Seuratlibrary(reticulate)Warning: package ‘reticulate’ was built under R version 4.3.1library(scrubletR)
library(ggplot2)
library(patchwork)
library(dplyr)
Attaching package: ‘dplyr’
The following objects are masked from ‘package:stats’:
filter, lag
The following objects are masked from ‘package:base’:
intersect, setdiff, setequal, unionlibrary(data.table)data.table 1.14.8 using 4 threads (see ?getDTthreads). Latest news: r-datatable.com
Attaching package: ‘data.table’
The following objects are masked from ‘package:dplyr’:
between, first, lastlibrary(clustree)Warning: package ‘clustree’ was built under R version 4.3.1Loading required package: ggraph
Warning: package ‘ggraph’ was built under R version 4.3.1library(reshape2)
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dcast, meltlibrary(tidyr)
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combinelibrary(stringr)Warning: package ‘stringr’ was built under R version 4.3.1library(plyr)------------------------------------------------------------------------------------------------------------------------------------------------------------------------
You have loaded plyr after dplyr - this is likely to cause problems.
If you need functions from both plyr and dplyr, please load plyr first, then dplyr:
library(plyr); library(dplyr)
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Attaching package: ‘plyr’
The following objects are masked from ‘package:dplyr’:
arrange, count, desc, failwith, id, mutate, rename, summarise, summarizesource("C:/Ryan/GitHub/trachtenberg-lab/transcriptomics/tools/seurat_functions.R")
source("C:/Ryan/GitHub/trachtenberg-lab/transcriptomics/tools/seurat_integration_functions.R")
source("C:/Ryan/GitHub/trachtenberg-lab/transcriptomics/xgboost/xgboost_train.R")
source("C:/Ryan/GitHub/trachtenberg-lab/transcriptomics/xgboost/plottingFxns.R")
obj.opossum.gabaergic <- readRDS("E:/Transcriptomics_V1/Opossum/seurat/opossum_v1_gabaergic_processed.rds")
obj.opossum.gabaergic$species <- "Opossum"
subclass.markers.opossum.gabaergic <- readRDS("E:/Transcriptomics_V1/Opossum/seurat/marker_genes/GABAergic/markerdict_subclass.rds")
markers.opossum.gabaergic <- readRDS("E:/Transcriptomics_V1/Opossum/seurat/marker_genes/GABAergic/markerdict_types.rds")
obj.mouse.gabaergic.P38 <- readRDS("E:/Transcriptomics_V1/Mouse/seurat/mouse_v1_P38_gabaergic_processed.rds")
obj.mouse.gabaergic.P38$species <- "Mouse"
subclass.markers.mouse.gabaergic.P38 <- readRDS("E:/Transcriptomics_V1/Mouse/seurat/marker_genes/GABAergic/P38/markerdict_subclass.rds")
markers.mouse.gabaergic.P38 <- readRDS("E:/Transcriptomics_V1/Mouse/seurat/marker_genes/GABAergic/P38/markerdict_types.rds")
objs <- list(obj.opossum.gabaergic, obj.mouse.gabaergic.P38)
subclass.markers <- list(subclass.markers.opossum.gabaergic, subclass.markers.mouse.gabaergic.P38)
type.markers <- list(markers.opossum.gabaergic, markers.mouse.gabaergic.P38)
sample.names <- list("OpossumV1", "MouseV1-P38")
subclasses <- c("Pvalb", "Sst", "Vip", "Lamp5", "Frem1", "Stac")
# pre-integration subclass comparison (DE genes)
for (pc in c(T, F)) {
p <- PlotSubclassDEIntersection(subclass.markers[[1]], subclass.markers[[2]],
rownames(objs[[1]]), rownames(objs[[2]]),
sample.names[[1]], sample.names[[2]],
subclasses, 0.2, "E:/Transcriptomics_V1/Integration/Opossum_Mouse-P38/subclass_markers/GABAergic/", percentage = pc)
print(p)
}Warning: NAs introduced by coercion to integer rangeWarning: NAs introduced by coercion to integer rangeWarning: Using `size` aesthetic for lines was deprecated in ggplot2 3.4.0.
Please use `linewidth` instead.
# pre-integration type comparison (DE genes)
for (pc in c(T, F)) {
for (sbcl in subclasses) {
if (sbcl %in% names(type.markers[[1]]) & sbcl %in% names(type.markers[[2]])) {
p <- PlotIdentDEIntersection(type.markers[[1]], type.markers[[2]],
rownames(objs[[1]]), rownames(objs[[2]]),
sample.names[[1]], sample.names[[2]],
sbcl, sbcl, "type", "type", 0.2, percentage = pc)
print(p)
}
}
}
sbcl_conf_plots <- PlotSubclassCrossConfusionMatrices(objs[[1]], objs[[2]],
sample.names[[1]], sample.names[[2]],
assay = "SCT",
subclasses, n_iters = 10, all.genes = FALSE, upsample = TRUE)Warning: NAs introduced by coercion to integer rangeWarning: NAs introduced by coercion to integer rangeWarning: package ‘xgboost’ was built under R version 4.3.1
Attaching package: ‘xgboost’
The following object is masked from ‘package:dplyr’:
slice
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print(sbcl_conf_plots[[1]])
print(sbcl_conf_plots[[2]])
subclass.labels <- c("Pvalb", "Sst", "Vip")
ident.labels <- c("type")
idnt_conf_plots <- PlotIdentCrossConfusionMatrices(objs[[1]], objs[[2]],
sample.names[[1]], sample.names[[2]],
assay = "SCT",
subclass.labels, ident.labels, n_iters = 10,
ident.genes = TRUE, all.genes = FALSE, upsample = TRUE)[1] "Using IntegrationFeatures from the Ident level..."
[1] "Using IntegrationFeatures from the Ident level..."
[1] "Using IntegrationFeatures from the Ident level..."
for (sbcl in subclass.labels) {
for (id in ident.labels) {
print(idnt_conf_plots[[sbcl]][[id]][["avg1"]])
print(idnt_conf_plots[[sbcl]][[id]][["avg2"]])
}
}
obj.integrated <- IntegrateObjects(objs[[1]], objs[[2]], resolutions = c(1, 2), nfeatures = 3000, subsample = TRUE)
| | 0 % ~calculating
|+++++++++++++++++++++++++ | 50% ~01s
|++++++++++++++++++++++++++++++++++++++++++++++++++| 100% elapsed=02s Finding all pairwise anchors
| | 0 % ~calculating Running CCA
Merging objects
Finding neighborhoods
Finding anchors
Found 4357 anchors
Filtering anchors
Retained 3444 anchors
|++++++++++++++++++++++++++++++++++++++++++++++++++| 100% elapsed=19s sct.model: model1
Setting min_variance based on median UMI: 0.04
Calculating residuals of type pearson for 6513 genes
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**************************************************|
Integrating data
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PlotIntegration(obj.integrated, "species", c("integrated_snn_res.1", "integrated_snn_res.2"), subclasses)
objs.i <- SplitObject(obj.integrated, split.by = "species")
sbcl_conf_plots_i <- PlotSubclassCrossConfusionMatrices(objs.i[[1]], objs.i[[2]],
sample.names[[1]], sample.names[[2]],
assay = "integrated",
subclasses, n_iters = 10, all.genes = FALSE, upsample = TRUE)Warning: NAs introduced by coercion to integer rangeWarning: NAs introduced by coercion to integer rangeWarning: NAs introduced by coercion to integer rangeWarning: NAs introduced by coercion to integer rangeWarning: NAs introduced by coercion to integer rangeWarning: NAs introduced by coercion to integer rangeWarning: NAs introduced by coercion to integer rangeWarning: NAs introduced by coercion to integer rangeWarning: NAs introduced by coercion to integer rangeWarning: NAs introduced by coercion to integer rangeWarning: NAs introduced by coercion to integer rangeWarning: NAs introduced by coercion to integer rangeWarning: NAs introduced by coercion to integer rangeWarning: NAs introduced by coercion to integer rangeWarning: NAs introduced by coercion to integer rangeWarning: NAs introduced by coercion to integer rangeWarning: NAs introduced by coercion to integer rangeWarning: NAs introduced by coercion to integer rangeWarning: NAs introduced by coercion to integer rangeWarning: NAs introduced by coercion to integer rangeWarning: NAs introduced by coercion to integer rangeWarning: NAs introduced by coercion to integer rangeWarning: NAs introduced by coercion to integer rangeWarning: NAs introduced by coercion to integer rangeWarning: NAs introduced by coercion to integer rangeWarning: NAs introduced by coercion to integer range
print(sbcl_conf_plots_i[[1]])
print(sbcl_conf_plots_i[[2]])
subclass.labels <- c("Pvalb", "Sst", "Vip")
ident.labels <- c("type")
idnt_conf_plots_i <- PlotIdentCrossConfusionMatrices(objs.i[[1]], objs.i[[2]],
sample.names[[1]], sample.names[[2]],
assay = "integrated",
subclass.labels, ident.labels, n_iters = 10,
ident.genes = TRUE, all.genes = FALSE, upsample = TRUE)[1] "Using IntegrationFeatures from the Ident level..."Warning: Not all features provided are in this Assay object, removing the following feature(s): Ush1c, Uaca, Ntsr1, Cdh16, Aldh1a3, Ltf, Cenpf, Trp63, Tdrd1, Ptpn20, Ndc80, Dlk1, Slc5a11, Vwa7, Commd1, Zhx1, Tnnt2, Ribc2, Fam178b, Cpz, Frem3, Shcbp1, Rnasek, Satl1, Pik3r5, Cnga3, Ghrh, Abcb6, Pdlim4, Bco1, Nr0b1, Bnc1, Tmem42, Cd4, Ebi3, Ptgr1, Tmem182, Cpvl, 1810020O05Rik, Fbln7, Kdelr3, Mael, Hhip, Obscn, Xrra1, Gm6657, Pkd1l1, Gadl1, Azgp1, Aspg, Tor4a, Ano7, Cyp27a1, Nme3, Tktl2, Rnase1, Tcea3, Tinag, Pudp, Chkb, Cel, Glipr2, Phf19, Rnf139, Ing4, Zfp488, Pbp2, Fermt1, Ppt2, Cd5, Dscc1, Mylk4, Pdzd9, Prnp, Ikzf1, Pik3ap1, Tm4sf20, Wnt9b, Alox15, Traf3ip3, Sec31b, Tcf7, Cbx6, Tpte, Catsper4, Klk11, Ccdc158, Zc3h11a, Lypla1Warning: Not all features provided are in this Assay object, removing the following feature(s): Ush1c, Uaca, Ntsr1, Cdh16, Aldh1a3, Ltf, Cenpf, Trp63, Tdrd1, Ptpn20, Ndc80, Dlk1, Slc5a11, Vwa7, Commd1, Zhx1, Tnnt2, Ribc2, Fam178b, Cpz, Frem3, Shcbp1, Rnasek, Satl1, Pik3r5, Cnga3, Ghrh, Abcb6, Pdlim4, Bco1, Nr0b1, Bnc1, Tmem42, Cd4, Ebi3, Ptgr1, Tmem182, Cpvl, 1810020O05Rik, Fbln7, Kdelr3, Mael, Hhip, Obscn, Xrra1, Gm6657, Pkd1l1, Gadl1, Azgp1, Aspg, Tor4a, Ano7, Cyp27a1, Nme3, Tktl2, Rnase1, Tcea3, Tinag, Pudp, Chkb, Cel, Glipr2, Phf19, Rnf139, Ing4, Zfp488, Pbp2, Fermt1, Ppt2, Cd5, Dscc1, Mylk4, Pdzd9, Prnp, Ikzf1, Pik3ap1, Tm4sf20, Wnt9b, Alox15, Traf3ip3, Sec31b, Tcf7, Cbx6, Tpte, Catsper4, Klk11, Ccdc158, Zc3h11a, Lypla1[1] "Using IntegrationFeatures from the Ident level..."
[1] "Using IntegrationFeatures from the Ident level..."
for (sbcl in subclass.labels) {
for (id in ident.labels) {
print(idnt_conf_plots_i[[sbcl]][[id]][["avg1"]])
print(idnt_conf_plots_i[[sbcl]][[id]][["avg2"]])
}
}
objs.m <- MapObjects(objs.i[[1]], objs.i[[2]], c("subclass", "type"), assay = "integrated")
source("C:/Ryan/GitHub/trachtenberg-lab/transcriptomics/tools/seurat_functions.R")
source("C:/Ryan/GitHub/trachtenberg-lab/transcriptomics/tools/seurat_integration_functions.R")
PlotMapping(objs.m, ident.order = subclasses)
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